A New Predictive Model for Radiation Necrosis Risk Based on PTV-Enriched Blood Inflammatory Biomarkers in Patients...

Area of Science:

• Oncology
• Radiotherapy
• Proteomics

Background:

• Radiation necrosis (RN) is a complication of stereotactic radiosurgery (SRS) for brain metastases (BMs).
• Planning target volume (PTV) is an imperfect predictor of RN.
• Inflammatory markers in peripheral blood may indicate radiation-induced brain injury.

Purpose of the Study:

• To identify predictive biomarkers for symptomatic RN.
• To develop a risk prediction model using inflammatory plasma markers and PTV.

Main Methods:

• Retrospective analysis of plasma samples from BMs patients treated with SRS or fractionated stereotactic radiotherapy (FSRT).
• Olink 96 Target Immuno-Oncology Panel used to analyze 92 proteins.
• Cox regression and ROC curve analyses performed to evaluate predictors of RN.

Main Results:

• Planning target volume (PTV), MUC-16, and CXCL11 were identified as independent predictors of RN.
• A high Necrosis Prediction Index (NPI) combining PTV with MUC-16 and CXCL11 significantly increased RN risk (HR=2.543).
• NPI achieved an AUC of 0.808 in distinguishing patients with RN.

Conclusions:

• The combination of PTV, CXCL11, and MUC-16 may predict RN development.
• Further validation of this predictive model is warranted.